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Neuroevolution in Go

Overview

For my CS344 Artificial Intelligence course final project, I wrote a neuroevolution algorithm in Golang. By treating the weights of neurons as dimensions of a search space, it attempts to evolve networks that are more capable of surviving in game playing environments. It has support for Tic Tac Toe and Checkers so far.

Usage

Usage of Neuroevolution.exe:

-filename string
    JSON file to load containing a neural network (default "None")

-game string
    Name of game to be played. Currently Tic Tac Toe and Checkers are supported. (default "Tic Tac Toe")

-generations int
    Number of generations to evolve before returning the best network (default 128)

-hiddens int
    Number of hidden neurons. Recommend 56 for Tic Tac Toe. (default 256)

-maxgames int
    Maximum number of games to play within a population (default 1024)

-output string
    Name of a JSON file to write the results to (default "data\\results.json")

-population int
    Number of individuals in the population (default 256)

-streak int
    Number of generations that achieve the maximum score before ending the algorithm early (default 4)

Repository

This project may be found at: https://github.com/CRRDerek/Neuroevolution.git